Scholar
Dr. Gerrit Großmann
Google Scholar ID: e27EmFsAAAAJ
DFKI, Saarland University
Citations & Impact
Citations
176
H-index
7
i10-index
4
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Publications, talks, and tutorials include: Generative AI for Drug Discovery, Language Models and Structured Knowledge in AI, Molecule Generation with Graph Neural Networks and Probabilistic Diffusion, (Neural) Spatio-Temporal Models tutorial, deep learning for computer-aided drug design tutorial series, etc.
Research Experience
- 2017: Part-time Deep Learning Engineer at iMAR Navigation GmbH; 2012-2017: Part-time Software Development/Data Analysis at the Cognitive Psychology group; 2023-Present: Team Lead for Spatio-temporal Modeling and Forecasting at the Data Science and its Applications group and Senior Researcher at DFKI.
Education
- 2006-2007: Attended Parkland Secondary School in British Columbia; 2010: High school degree at OzD in Lübeck; 2010-2018: Bachelor's and Master's degrees in Computer Science at Saarland University; 2019-2022: PhD (Dr. rer. nat) in Computer Science at the Modeling and Simulation group at Saarland University. Advisor information not provided.
Background
- Research Interests: Integration of discrete structures (such as graphs and networks) with the continuous nature of dynamic evolution, diffusion, and learning; developing numerical methods to analyze spatio-temporal and stochastic dynamical processes, understanding how a network shapes collective phenomena; geometric deep learning for molecules, particularly probabilistic flow models; neuro-symbolic guidance of diffusion models, semi-supervised learning on metabolic networks, expressiveness of message-passing architectures, and non-parametric methods for network reconstruction.
Miscellany
- Participates in STAR: Space × Time × Causality Reading Group; Mentor at AI Grid.
Co-authors